Systems and methods to automate slice admission control

ABSTRACT

A device may include a processor configured to receive a request to admit a network slice, associated with at least one requirement, in a wireless communication network. The processor may be further configured to determine a resources, associated with the wireless communication network, needed to implement the network slice; compute an estimated resource load for the network slice; compute a projected resource load for the determined resources; and determine that the resources have sufficient capacity to meet the at least one requirement associated with the network slice based on the computed estimated resource load and the projected resource load for the resources. The processor may admit the network slice to be deployed in the wireless communication network, in response to determining that the resources have sufficient capacity to meet the at least one requirement associated with the network slice.

BACKGROUND INFORMATION

To satisfy the needs and demands of users of mobile communicationdevices, providers of wireless communication services continue toimprove and expand available services as well as networks used todeliver such services. One aspect of such improvements includes thevirtualization of the components of wireless communications networks. Awireless communications network may provide different types of servicesto a large number of devices under various types of conditions. Managingvirtualized components to service a large number of different servicesor handle a large number of different conditions poses variouschallenges.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an environment according to an implementationdescribed herein;

FIG. 2 illustrates exemplary components of device that may be includedin the components of FIG. 1 according to an implementation describedherein;

FIG. 3 illustrates exemplary components of the orchestration system ofFIG. 1 according to an implementation described herein;

FIG. 4 illustrates exemplary components of the slice profile database ofFIG. 3 according to an implementation described herein;

FIG. 5 illustrates exemplary components of the network function databaseof FIG. 3 according to an implementation described herein;

FIG. 6 illustrates exemplary components of the virtual link database ofFIG. 3 according to an implementation described herein;

FIG. 7 illustrates a flowchart of a process for network slice admissionaccording to an implementation described herein;

FIG. 8 illustrates an exemplary set of network infrastructures andnetwork slices according to an implementation described herein; and

FIG. 9 illustrates an exemplary signal flow diagram according to animplementation described herein.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

The following detailed description refers to the accompanying drawings.The same reference numbers in different drawings identify the same orsimilar elements.

As communication networks and services increase in size, complexity, andnumber of users, management of the communication networks has becomeincreasingly more complex. One way in which wireless networks arecontinuing to become more complicated is by incorporating variousaspects of next generation networks, such as 5^(th) generation (5G)mobile networks, utilizing high frequency bands (e.g., 24 Gigahertz, 39GHz, etc.), and/or lower frequency bands such as Sub 6 GHz, and a largenumber of antennas. 5G New Radio (NR) radio access technology (RAT) mayprovide significant improvements in higher bandwidth and/or lowerlatency over other wireless network technology. Additionally, a 5G corenetwork supports and manages 5G radio access networks (RAN) that includebase stations, providing various services and enabling connections toother networks (e.g., connections to the Internet, etc.). As an example,a 5G core network may provide support for enhanced Mobile Broadband(eMBB), ultra reliable low latency communication (URLLC), massiveMachine Type Communication (mMTC), and/or other types of communications.

Such different types of services may be implemented using networkslicing. Network slicing is a form of virtual network architecture thatenables multiple logical networks to be implemented on top of a commonshared physical infrastructure using software defined networking (SDN)and/or network function virtualization (NFV). Each logical network,referred to as a “network slice,” may encompass an end-to-end virtualnetwork with dedicated storage and/or computation resources, may beconfigured to implement a different set of requirements and/orpriorities, and/or may be associated with a particular Class of Service(CoS) class, and/or particular enterprise customer associated with a setof user equipment (UE) devices.

In order to implement functionality such as, for example, networkslicing, a 5G core network may include various network nodes, known asnetwork functions (NFs). As the number of different NF types anddeployed instances of each NF continues to increase, the use ofvirtualized NFs (VNFs) has become more prevalent. VNF representations ofnetwork devices and/or nodes may be implemented using, for example, aEuropean Telecommunications Standards Institute (ETSI) network functionvirtualization (NFV) management and organization (MANO) architecture andmay be referred to as VNF managed objects (VNF MOs). VNF MOs may bedeployed, for example, on hardware in a cloud computing center. Incontrast to specialized hardware, which may be costly, time-consuming todeploy, difficult to scale, and/or labor-intensive to manage, NFV mayenable network entities to be implemented on standardized hardware,resulting in lower deployment and/or maintenance costs, as well as bringhigher flexibility compared to dedicated hardware implementations. Forexample, a VNF may be implemented on a hardware component that is partof a common shared physical infrastructure used to implement VNFinstances using Software Defined Networking (SDN) or another type ofvirtualization technique. The common shared physical infrastructure maybe implemented using computer devices in a cloud computing center, amulti-access edge computing (MEC) system associated with a base station,and/or in another type of computer system.

In some implementations, VNFs may be deployed using virtual machines.Virtual machines are generated on a physical architecture using avirtual machine monitor, also referred to as a hypervisor. Each virtualmachine runs its own instance of an operating system (OS), libraries,binary executable files, etc. In other implementations, VNFs may bedeployed using container-based virtualization, which enables multipleisolated user space instances to use the same OS instance and/or kernelspace. The isolated user space instances are referred to as containers.A container may have its own set of libraries and binary executablefiles, and/or its own dedicated share of hardware resources, but mayshare a kernel space with other containers. Since containers aredecoupled from the underlying infrastructure, containers may be portableacross cloud center and OS distributions. Furthermore, the functions ofan NF may be divided into microservices implemented in differentcontainers. An NF deployed using containers may be referred to as aCloud-Native Function (CNF).

A provider of wireless communication services may manage a set ofdifferent infrastructures and each infrastructure may host VNFs, as wellas virtual links between VNFs, to implement a set of network slices. Forexample, an eMBB infrastructure may host VNFs to implement a networkslice for voice communication using an Internet Protocol (IP) MultimediaSubsystem (IMS) and a network slice for video streaming. A low latencycommunication (LLC) infrastructure may host VNFs to implement aVehicle-to-Everything (V2X) network slice and a mission critical (MC)LLC network slice. Each network slice may be associated with a differentset of requirements, such as performance requirements, capacityrequirements, security requirements, etc.

As the number of network slices in a wireless communication networkincreases, managing the network slices may become complex and consume alarge amount of resources. For example, when a new network slice is tobe admitted to the wireless communication network, a determination mayneed to be made as to whether the network can meet service levelagreements (SLAs) associated with the new network slice. Thus,automating network slice admission control in an orchestration frameworkfor a wireless communication network may be a requirement to efficientlymeet SLAs, assure performance, and enable on-demand rapid serviceoffering and deployment of network slices.

Implementations described herein relate to systems and methods forautomated slice admission control. An orchestration system may receive arequest to admit a network slice in a wireless communication network.The orchestration system may determine requirements associated with thenetwork slice, such as, for example, a performance requirement, acapacity requirement, and/or a security requirement, and select aninfrastructure on which to deploy the network slice, such as, forexample, an eMBB infrastructure, an LLC infrastructure, an ultra-lowlatency communication (U-LLC) infrastructure, etc.

The orchestration system may determine NFs, and virtual links betweenthe NFs, which are needed to implement the network slice and thendetermine resources associated with the NFs and virtual links, includingresources used by an NF and/or resources controlled by an NF. Theresources may include cloud resources, transport resources, and/or radioaccess network (RAN) resources. The orchestration system may compute anestimated resource load for the network slice design and compute aprojected resource load for the determined resources. Determining theprojected resource load may include determining a current load for theresources based on a set of metrics associated with the resources andcomputing an estimated future load for resources based on a historicalload associated with the resources.

The orchestration system may then determine whether the resources havesufficient capacity to meet the requirements associated with the networkslice based on the estimated resource load for the network slice, theprojected resource load for the determined resources, and the admissioncriteria associated with the selected infrastructure. If theorchestration system determines that the resources have sufficientcapacity to meet the requirements associated with the network slice, theorchestration system may admit the network slice to be deployed in thewireless communication network and the network slice may be deployed onthe selected infrastructure. If the orchestration system determines thatthe resources do not have sufficient capacity to meet the requirementsassociated with the network slice, the orchestration system may generatea message indicating the network slice cannot be admitted. Additionally,or alternatively, the orchestration system may select a differentinfrastructure and repeat the admission process using the differentinfrastructure.

FIG. 1 is a diagram of an exemplary environment 100 in which the systemsand/or methods, described herein, may be implemented. As shown in FIG.1, environment 100 may include UE devices 110-A to 110-N (referred toherein collectively as “UE devices 110” and individually as “UE device110”), radio access network (RAN) 130 that includes base stations 120-Ato 120-X (referred to herein collectively as “base stations 120” andindividually as “base station 120”), MEC network(s) 140 that include MECdevice(s) 145, core network 150 that includes network device(s) 160, anordering system 165, an orchestration system 170, a deployment system180, and an analytics system 185, and packet data networks (PDNs) 190-Ato 190-Y (referred to herein collectively as “PDNs 190” and individuallyas “PDN 190”).

UE device 110 may include any device with cellular wirelesscommunication functionality. For example, UE device 110 may include ahandheld wireless communication device (e.g., a mobile phone, a smartphone, a tablet device, etc.); a wearable computer device (e.g., ahead-mounted display computer device, a head-mounted camera device, awristwatch computer device, etc.); a laptop computer, a tablet computer,or another type of portable computer; a desktop computer; a customerpremises equipment (CPE) device, such as a set-top box or a digitalmedia player (e.g., Apple TV, Google Chromecast, Amazon Fire TV, etc.),a WiFi access point, a smart television, etc.; a portable gaming system;a global positioning system (GPS) device; a home appliance device; ahome monitoring device; and/or any other type of computer device withwireless communication capabilities and a user interface. UE device 110may include capabilities for voice communication, mobile broadbandservices (e.g., video streaming, real-time gaming, premium Internetaccess etc.), best effort data traffic, and/or other types ofapplications.

In some implementations, UE device 110 may communicate usingmachine-to-machine (M2M) communication, such as MTC, and/or another typeof M2M communication for Internet of Things (IoT) applications. Forexample, UE device 110 may include a health monitoring device (e.g., ablood pressure monitoring device, a blood glucose monitoring device,etc.), an asset tracking device (e.g., a system monitoring thegeographic location of a fleet of vehicles, etc.), a traffic managementdevice (e.g., a traffic light, traffic camera, road sensor, roadillumination light, etc.), a climate controlling device (e.g., athermostat, a ventilation system, etc.), a device controlling anelectronic sign (e.g., an electronic billboard, etc.), a devicecontrolling a manufacturing system (e.g., a robot arm, an assembly line,etc.), a device controlling a security system (e.g., a camera, a motionsensor, a window sensor, etc.), a device controlling a power system(e.g., a smart grid monitoring device, a utility meter, a faultdiagnostics device, etc.), a device controlling a financial transactionsystem (e.g., a point-of-sale terminal, an automated teller machine, avending machine, a parking meter, etc.), and/or another type ofelectronic device.

Base station 120 may include a 5G NR base station (e.g., a gNodeB)and/or a Fourth Generation (4G) Long Term Evolution (LTE) base station(e.g., an eNodeB). Each base station 120 may include devices and/orcomponents configured to enable cellular wireless communication with UEdevices 110. For example, base station 120 may include a radio frequency(RF) transceiver configured to communicate with UE devices using a 5G NRair interface using a 5G NR protocol stack, a 4G LTE air interface usinga 4G LTE protocol stack, and/or using another type of cellular airinterface. Base station 120 may enable communication with core network150 to enable core network 150 to authenticate UE device 110 with asubscriber management device (e.g., Home Subscriber Server (HSS) in 4G,Unified Data Management (UDM) in 5G, etc.).

RAN 130 may enable UE devices 110 to connect to core network 150 viabase stations 120 using cellular wireless signals. For example, RAN 130may include one or more central units (CUs) and distributed units (DUs)(not shown in FIG. 1) that enable and manage connections from basestations 120 to core network 150. RAN 130 may include featuresassociated with an LTE Advanced (LTE-A) network and/or a 5G core networkor other advanced network, such as management of 5G NR base stations;carrier aggregation; advanced or massive multiple-input andmultiple-output (MIMO) configurations (e.g., an 8×8 antennaconfiguration, a 16×16 antenna configuration, a 256×256 antennaconfiguration, etc.); cooperative MIMO (CO-MIMO); relay stations;Heterogeneous Networks (HetNets) of overlapping small cells andmacrocells; Self-Organizing Network (SON) functionality; MTCfunctionality, such as 1.4 Megahertz (MHz) wide enhanced MTC (eMTC)channels (also referred to as category Cat-M1), Low Power Wide Area(LPWA) technology such as Narrow Band (NB) IoT (NB-IoT) technology,and/or other types of MTC technology; and/or other types of LTE-A and/or5G functionality.

Each MEC network 140 may be associated with one or more base stations120 and may provide MEC services for UE devices 110 attached to the oneor more base stations 120. MEC network 140 may be in proximity to theone or more base stations 120 from a geographic and network topologyperspective, thus enabling low latency communication with UE devices 110and/or base stations 120. As an example, MEC network 140 may be locatedon a same site as one of the one or more base stations 120. As anotherexample, MEC network 140 may be geographically closer to the one or morebase stations 120, and reachable via fewer network hops and/or fewerswitches, than other base stations 120 and/or packet data networks 190.As yet another example, MEC network 140 may be reached without having togo through a gateway device, such as a 4G Packet Data Network Gateway(PGW) or a 5G User Plane Function (UPF).

MEC network 140 may include one or more MEC devices 145. MEC devices 145may provide MEC services to UE devices 110, such as, for example,content delivery of streaming audio and/or video, cloud computingservices, authentication services, etc. In some implementations, MECdevices 145 may host deployed VNFs used to implement particular networkslices. Thus, MEC devices 145 may form part of an infrastructure forhosting network slices. For example, an LLC infrastructure may enableVNFs to be implemented in a first MEC network 140 that includes MECdevices 145 accessible via a PGW or UPF connection, while a U-LLCinfrastructure may enable VNFs to be implemented in a second MEC network140 that includes MEC devices 145 accessible without having to establisha connection via a PGW or UPF, by enabling a direct connection from basestation 120 to MEC device 145.

Core network 150 may be managed by a provider of cellular wirelesscommunication services and may manage communication sessions ofsubscribers connecting to core network 150 via RAN 130. For example,core network 150 may establish an Internet Protocol (IP) connectionbetween UE devices 110 and PDN 190. In some implementations, corenetwork 150 may include a 5G core network. A 5G core network may includedevices that implement network functions that include an Access andMobility Function (AMF) to perform registration management, connectionmanagement, reachability management, mobility management, and/or lawfulintercepts; a Session Management Function (SMF) to perform sessionmanagement, session modification, session release, IP allocation andmanagement, Dynamic Host Configuration Protocol (DHCP) functions, andselection and control of a UPF; a UPF to serve as a gateway to packetdata network 190, act as an anchor point, perform packet inspection,routing, and forwarding, perform Class of Service (CoS) handling in theuser plane, uplink traffic verification, transport level packet marking,downlink packet buffering, and/or other type of user plane functions; anApplication Function (AF) to provide services associated with aparticular application; a Unified Data Management (UDM) to managesubscription information, handle user identification and authentication,and perform access authorization; a Policy Control Function (PCF) tosupport policies to control network behavior, provide policy rules tocontrol plane functions, access subscription information relevant topolicy decisions, and perform policy decisions; a Charging Function(CHF) to perform charging and billing functions; a Network RepositoryFunction (NRF) to support service discovery, registration of networkfunction instances, and maintain profiles of available network functioninstances; a Network Exposure Function (NEF) to expose capabilities andevents to other network functions, including third party networkfunctions; a Network Slice Selection Function (NSSF) to select a networkslice instance to serve a particular UE device 110; a Network DataAnalytics Function (NWDAF) to collect analytics information, such as,for example, a set of Key Performance Indicator (KPI) values associatedwith RAN 130 and/or core network 150; and/or other types of networkfunctions.

In other implementations, core network 150 may include a 4G LTE corenetwork (e.g., an evolved packet core (EPC) network). An EPC network mayinclude devices that implement network functions that include a MobilityManagement Entity (MME) for control plane processing, authentication,mobility management, tracking and paging, and activating anddeactivating bearers; a Serving Gateway (SGW) that provides an accesspoint to and from UE devices, acts as a local anchor point duringhandovers, and directs gateway to a PDN gateway (PGW); a PGW thatfunctions as a gateway to a particular PDN 190; a Policy and ChargingRules Function (PCRF) that implements policy and charging rulesfunctions, such as establishment of Quality of Service (QoS)requirements, setting allowed bandwidth and/or data throughput limitsfor particular bearers, and/or other policies; and a Home SubscriberServer (HSS) that stores subscription information for UE devices,including subscription profiles that include authentication and accessauthorization information, group device memberships, subscriptionprivileges, and/or other types of subscription information.

Core network 150 may include network device(s) 160. Network device 160may include a 4G network node; a 5G NF; a transport network device, suchas, for example, a switch, router, firewall, gateway, an opticalswitching device (e.g., a reconfigurable optical add-drop multiplexer,etc.), and/or another type of network device. Network device 160 mayinclude a physical function node or a VNF. Thus, the components of corenetwork 150 may be implemented as dedicated hardware components and/oras VNFs implemented on top of a common shared physical infrastructureusing Software Defined Networking (SDN). For example, an SDN controller(e.g., in deployment system 180) may implement one or more of thecomponents of core network 150 using an adapter implementing a VNFvirtual machine, a Cloud-Native Network Function (CNF) container, anevent driven serverless architecture interface, and/or another type ofSDN architecture. The common shared physical infrastructure may beimplemented using one or more devices 200 described below with referenceto FIG. 2 in a cloud computing center associated with core network 150.Additionally, or alternatively, some, or all, of the common sharedphysical infrastructure may be implemented using one or more devices 200included in MEC device 145. Sets of network devices 160 and/or MECdevices 145 may be organized into different infrastructures. As anexample, an eMBB infrastructure may include network devices 160 thatfunction as gateway devices (e.g., UPFs, PGWs, etc.) to packet datanetworks 190 a low latency infrastructure may include VNFs implementedin MEC devices 145, etc.

Ordering system 165 may include one or more computer devices, such asserver devices, to process orders for network slices. For example, acustomer, such as a business, organization, and/or government entity mayrequest a service for which a new network slice is to be deployed. As anexample, a business may request a communication service associated witha QoS and may request data traffic separation for the service, resultingin ordering system 165 sending a request, to admit a new network slicein core network 150 and/or RAN 130, to orchestration system 170.

Orchestration system 170 may include one or more computer devices, suchas server devices, to orchestrate network slices in core network 150and/or RAN 130. For example, orchestration system 170 may determinewhether a particular network slice should be admitted and deployed on aparticular infrastructure. Orchestration system 170 may admit a networkslice based on requirements associated with the network slice, based onan estimated load associated with the network slice, and/or based on aprojected load for resources required to implement the network slice.Orchestration system 170 may obtain current and/or projected load forresources required to implement the slice from analytics system 185.Furthermore, in some implementations, orchestration system 170 maydetermine whether a VNF instance in core network 150 is to be created,deleted, and/or modified, whether a new type of VNF instance needs to beadded to core network 150. Orchestration system 170 may sendinstructions to deployment system 180 to deploy VNFs and/or to deploynetwork slices on particular VNFs.

Deployment system 180 may include one or more computer devices, such asserver devices, to deploy VNFs in core network 150 and/or RAN 130,and/or to configure the deployed VNFs to implement network slices, basedon instructions received from orchestration system 170. For example,deployment system 180 may include a container orchestration platform toconfigure and automate VNF deployment, scaling, and/or management. Forexample, the container orchestration platform may deploy a VNF as a setof microservices, with each microservice deployed in a differentcontainer, may deploy additional instances of an VNF based on increasedload, and/or may manage the deployed instances across different physicaldevices, referred to as nodes. Furthermore, deployment system 180 maymanage communication between different microservices using a servicemesh. The container orchestration platform may organize containers intogroups called pods and the service mesh may deploy a service proxy inthe same pod as a microservice container to enable the microservice tocommunicate with other microservices.

Analytics system 185 may include one or more computer devices, such asserver devices, to collect KPI metrics associated with VNFs and/orvirtual links between VNFs in core network 150 and/or RAN 130. Forexample, analytics system 185 may include an NWDAF and/or may obtain KPIvalues obtained by an NWDAF for VNFs in core network 150. Furthermore,analytics system 185 may obtained KPI values from base stations 120 andor transport network devices such as routers, switches, etc. Thecollected KPI values may be used by analytics system 185 to determinecurrent load values for resources associated with core network 150and/or RAN 130. Furthermore, analytics system 185 may compute aprojected future load for resources associated with core network 150and/or RAN 130 based on historical load values associated with theresources. For example, analytics system 185 may include a machinelearning model trained to estimate future loads based on historicalvalues associated with particular resources.

PDNs 190-A to 190-N may each include a packet data network. A particularPDN 190 may be associated with an Access Point Name (APN) and UE device110 may request a connection to the particular packet data network 190using the APN. PDN 190 may include, and/or be connected to and enablecommunication with, a local area network (LAN), a wide area network(WAN), a metropolitan area network (MAN), an autonomous system (AS) onthe Internet, an optical network, a cable television network, asatellite network, a wireless network (e.g., a CDMA network, a generalpacket radio service (GPRS) network, and/or an LTE network), an ad hocnetwork, a telephone network (e.g., the Public Switched TelephoneNetwork (PSTN) or a cellular network), an intranet, or a combination ofnetworks.

Although FIG. 1 shows exemplary components of environment 100, in otherimplementations, environment 100 may include fewer components, differentcomponents, differently arranged components, or additional componentsthan depicted in FIG. 1. Additionally, or alternatively, one or morecomponents of environment 100 may perform functions described as beingperformed by one or more other components of environment 100. Forexample, while ordering system 165, orchestration system 170, deploymentsystem 180, and analytics system 185 are shown as separate systems inFIG. 1, in other implementations, orchestration system 170 may includeand/or be combined with any of ordering system 165, deployment system180, and/or analytics system 185.

FIG. 2 is a diagram illustrating example components of a device 200according to an implementation described herein. UE device 110, basestation 120, MEC device 145, network device 160, ordering system 165,orchestration system 170, deployment system 180, and/or analytics system185 may each include, or be implemented on, one or more devices 200. Asshown in FIG. 2, device 200 may include a bus 210, a processor 220, amemory 230, an input device 240, an output device 250, and acommunication interface 260.

Bus 210 may include a path that permits communication among thecomponents of device 200. Processor 220 may include any type ofsingle-core processor, multi-core processor, microprocessor, latch-basedprocessor, central processing unit (CPU), graphics processing unit(GPU), tensor processing unit (TPU), hardware accelerator, and/orprocessing logic (or families of processors, microprocessors, and/orprocessing logics) that interprets and executes instructions. In otherembodiments, processor 220 may include an application-specificintegrated circuit (ASIC), a field-programmable gate array (FPGA),and/or another type of integrated circuit or processing logic.

Memory 230 may include any type of dynamic storage device that may storeinformation and/or instructions, for execution by processor 220, and/orany type of non-volatile storage device that may store information foruse by processor 220. For example, memory 230 may include a randomaccess memory (RAM) or another type of dynamic storage device, aread-only memory (ROM) device or another type of static storage device,a content addressable memory (CAM), a magnetic and/or optical recordingmemory device and its corresponding drive (e.g., a hard disk drive,optical drive, etc.), and/or a removable form of memory, such as a flashmemory.

Input device 240 may allow an operator to input information into device200. Input device 240 may include, for example, a keyboard, a mouse, apen, a microphone, a remote control, an audio capture device, an imageand/or video capture device, a touch-screen display, and/or another typeof input device. In some implementations, device 200 may be managedremotely and may not include input device 240. In other words, device200 may be “headless” and may not include a keyboard, for example.

Output device 250 may output information to an operator of device 200.Output device 250 may include a display, a printer, a speaker, and/oranother type of output device. For example, device 200 may include adisplay, which may include a liquid-crystal display (LCD) for displayingcontent to the user. In some implementations, device 200 may be managedremotely and may not include output device 250. In other words, device200 may be “headless” and may not include a display, for example.

Communication interface 260 may include a transceiver that enablesdevice 200 to communicate with other devices and/or systems via wirelesscommunications (e.g., radio frequency, infrared, and/or visual optics,etc.), wired communications (e.g., conductive wire, twisted pair cable,coaxial cable, transmission line, fiber optic cable, and/or waveguide,etc.), or a combination of wireless and wired communications.Communication interface 260 may include a transmitter that convertsbaseband signals to radio frequency (RF) signals and/or a receiver thatconverts RF signals to baseband signals. Communication interface 260 maybe coupled to an antenna for transmitting and receiving RF signals.

Communication interface 260 may include a logical component thatincludes input and/or output ports, input and/or output systems, and/orother input and output components that facilitate the transmission ofdata to other devices. For example, communication interface 260 mayinclude a network interface card (e.g., Ethernet card) for wiredcommunications and/or a wireless network interface (e.g., a WiFi) cardfor wireless communications. Communication interface 260 may alsoinclude a universal serial bus (USB) port for communications over acable, a Bluetooth™ wireless interface, a radio-frequency identification(RFID) interface, a near-field communications (NFC) wireless interface,and/or any other type of interface that converts data from one form toanother form.

As will be described in detail below, device 200 may perform certainoperations relating to automated network slice admission control. Device200 may perform these operations in response to processor 220 executingsoftware instructions contained in a computer-readable medium, such asmemory 230. A computer-readable medium may be defined as anon-transitory memory device. A memory device may be implemented withina single physical memory device or spread across multiple physicalmemory devices. The software instructions may be read into memory 230from another computer-readable medium or from another device. Thesoftware instructions contained in memory 230 may cause processor 220 toperform processes described herein. Alternatively, hardwired circuitrymay be used in place of, or in combination with, software instructionsto implement processes described herein. Thus, implementations describedherein are not limited to any specific combination of hardware circuitryand software.

Although FIG. 2 shows exemplary components of device 200, in otherimplementations, device 200 may include fewer components, differentcomponents, additional components, or differently arranged componentsthan depicted in FIG. 2. Additionally, or alternatively, one or morecomponents of device 200 may perform one or more tasks described asbeing performed by one or more other components of device 200.

FIG. 3 is a diagram illustrating exemplary components of orchestrationsystem 180. The components of orchestration system 180 may beimplemented, for example, via processor 220 executing instructions frommemory 230. Alternatively, some or all of the components oforchestration system 180 may be implemented via hard-wired circuitry. Asshown in FIG. 3, orchestration system 180 may include an ordering systeminterface 310, a slice profile database (DB) 320, a slice admissionmanager 330, a load estimator 340, a network function database (DB) 350,a virtual link DB 360, an infrastructure DB 370, a load metricsinterface 380, an admission criteria DB 385, and a deployment systeminterface 390.

Ordering system interface 310 may be configured to communicate withordering system 165. For example, ordering system interface 310 mayreceive a request to admit a new network slice and may store informationrelating to the new network slice in slice profile DB 320. The networkslice request may include information identifying one or morerequirements associated with the network slice. Exemplary informationthat may be stored in slice profile DB 320 is described below withreference to FIG. 4.

Slice admission manager 330 may select a particular infrastructure forthe new network slice based on the one or more requirements associatedwith the network slice and based on information stored in infrastructureDB 370. Infrastructure DB 370 may store information relating toparticular infrastructures associated with core network 150 and/or RAN130. For each infrastructure, infrastructure DB 370 may storeinformation identifying a geographic area associated with theinfrastructure, a type of service associated with the infrastructure, aperformance assurance associated with the infrastructure (e.g., alatency assurance, a reliability assurance, etc.), a capacity associatedwith the infrastructure, a security level associated with theinfrastructure, and/or other types of information that may be used byslice admission manager 330 to select a particular infrastructure onwhich to deploy a network slice. Furthermore, infrastructure DB 370 mayidentify a set of VNFs and/or virtual links between VNFs associated withthe infrastructure.

Slice admission manager 330 may identify resources required to implementthe network slice on the selected infrastructure. For example, sliceadmission manager 330 may identify an AMF, SMF, UPF, PCF, UDM, and/orother types of VNFs required to enable the network slice to enablecommunication between UE devices 110, between UE device 110 and packetdata network 190, between UE device 110 and MEC network 140, and/or toestablish other types of Protocol Data Unit (PDU) connections using theselected infrastructure. Furthermore, slice admission manager 330 mayidentify the virtual links between the selected VNFs. Slice admissionmanager 330 may then instruct load estimator 340 to determine anestimated load for the new network slice and a projected resource loadfor the identified resources required to implement the network slice.

Load estimator 340 may determine an estimated load for a network slicebased on a capacity requirement associated with the network slice. Thecapacity requirement may specify a UE device density for a geographicarea, a number of UE sessions during a particular time period, an uplinkand/or downlink throughput per UE device session, and/or another typesof capacity requirement. Load estimator 340 may convert the capacityrequirement into an estimated load for the network slice with respect tocloud resources, transport resources, and/or RAN resources. Loadestimator 340 may determine an average load, and/or a maximum load forthe cloud resources, transport resources, and/or RAN resources that maybe consumed by the network slice.

As an example, for the RAN resources, load estimator 340 may compute anaverage and/or maximum number of UE device connections per base stationsector for the network slice, an average and/or maximum carrierbandwidth for the network slice, an estimated carrier spectralefficiency for the network slice, and/or other types of RAN resourceloads. As another example, for transport resources, load estimator 340may compute an average and/or maximum number of carriers beingaggregated onto a circuit for the network slice, an average and/ormaximum number of connections per switch or router for the networkslice, and/or other types of transport resource loads. As yet anotherexample, for cloud resources, load estimator 340 may compute the averageand/or maximum processor and memory loads per session for the networkslice, a total average and/or maximum processor and memory load for thenetwork slice, and/or other types of cloud resource loads.

Furthermore, load estimator 340 may determine a projected resource loadfor the resources required to implement the network slice based onalready existing network slices. The projected resource load may bebased on a current load and/or a projected future load for the resourcerequired to implement the network slice. Load estimator 340 maydetermine the current load for the VNFs and/or virtual links between theVNFs identified by slice admission manager 330 for implementing thenetwork slice. As an example, for RAN resources controlled by a VNF,load estimator 340 may determine a number of UE device sessionsassociated with the RAN resources, a throughput associated with the RANresources, a spectral efficiency associated with the RAN resources,and/or other KPI values indicative of a resource load. As anotherexample, for cloud resources used by a NF, load estimator 340 maydetermine processor and/or memory resources being used by the VNF. Asyet another example, for a virtual link between two VNFs, load estimator340 may determine the transport resources being consumed by the virtuallink, such as a number of connection being handled by the virtual link,the throughput associated with the virtual link, the processingresources of a router or switch being consumed by the virtual link,and/or other transport network KPI values indicative of a resource load.

Load estimator 340 may obtain the KPI values for the current loads forthe VNFs and/or virtual links from load metrics interface 380 and storethe information in network function DB 350 and/or virtual link DB 360.Load metrics interface 380 may be configured to obtain the KPI valuesfrom analytics engine 190, from a particular NF, such as an NWDAF, froma service mesh configured to collect the KPI values via a service proxycontainer, and/or directly from particular VNF. Additionally, loadmetrics interface 380 may obtain projected future KPI values for loadsfor the VNFs and/or virtual links from analytics system 185.Alternatively, load estimator 340 may compute the projected future KPIvalues using a trained machine learning model based on historical loadvalues associated with the VNFs and/or virtual links and stored innetwork function DB 350 and/or virtual link DB 360. Exemplaryinformation that may be stored in network function DB 350 is describedbelow with reference to FIG. 5. Exemplary information that may be storedin virtual link DB 360 is described below with reference to FIG. 6.

Slice admission manager 330 may then determine whether to admit thenetwork slice based on the determined estimated resource load for thenetwork slice and the projected resource load for the resources requiredto implement the network slice. Slice admission manager 330 maydetermine a total resource load for the resources by adding theestimated resource load for the network slice and the projected resourceload for the resources, compare the total resource load to the totalcapacity of the resources, and determine whether comparison satisfiesone or more admission criteria stored in admission criteria DB 385.

Admission criteria DB 385 may store admission criteria for particularinfrastructures, particular classes of service, particular geographicareas, particular types of resources, etc. For example, an admissioncriterion may specify that a particular VNF associated with a particularinfrastructure may need to maintain a particular percentage of totalcapacity available to handle temporary spikes in the load. If admittinga network slice would result in the particular VNF having a smallerreserve capacity than specified by the admission criterion, the networkslice may not be admitted. Thus, slice admission manager 330 maydetermine whether admitting the network slice would result in anacceptable available capacity for the resources required to implementthe network slice and may admit the network slice if the admissioncriteria are satisfied. If the admission criteria are not satisfied,slice admission manager 330 may generate a message indicating thenetwork slice cannot be admitted and may send the error message toordering system 165. In some implementations, slice admission manager330 may select a different, less preferred infrastructure and attempt toadmit the network slice on the less preferred infrastructure. Forexample, slice admission manager 330 may select a regionalinfrastructure associated with a different geographic area, aninfrastructure associated with a different performance and/or capacityrequirement, etc.

Deployment system interface 390 may be configured to communicate withdeployment system 180. For example, deployment system interface 390 mayinstruct deployment system 180 to deploy a network slice after sliceadmission manager 330 selects to admit the network slice.

Although FIG. 3 shows exemplary components of orchestration system 180,in other implementations, orchestration system 180 may include fewercomponents, different components, additional components, or differentlyarranged components than depicted in FIG. 3. Additionally, oralternatively, one or more components of orchestration system 180 mayperform one or more tasks described as being performed by one or moreother components of orchestration system 180.

FIG. 4 illustrates exemplary components of slice profile DB 320. Asshown in FIG. 4, slice profile DB 320 may include one or more sliceprofile records 400. Each slice profile record 400 may store informationassociated with a particular network slice. Slice profile record 400 mayinclude a slice identifier (ID) field 410, requirements fields 420,infrastructure field 430, network functions field 440, virtual linksfield 450, and an estimated slice load field 460.

Slice ID field 410 may include a slice identifier associated with anetwork slice for which an admission determination is to be made. Forexample, slice ID field 410 may include a Network Slice SelectionAssistance Information (NSSAI) value, a Slice/Service Type (SST) value,a Slice Differentiation (SD) value, and/or another type network sliceidentification value.

Requirements fields 420 may store one or more requirements associatedwith the network slice. For example, requirements fields 420 may includea performance requirements field 422, a capacity requirements field 424,and/or a security requirements field 426. Performance requirements field422 may store information identifying one or more performancerequirements associated with the network slice, such as, for example, alatency requirement, a CoS requirement, a reliability requirement, anavailability requirement, a signal coverage requirement, a protocolsupport requirement, and/or another type of performance requirement.Capacity requirements field 424 may store information identifying one ormore capacity requirements associated with the network slice, such as,for example, a number of UE device sessions requirement, a throughputper UE device session requirement, a total throughput requirement,and/or another type of capacity requirement. Security requirements field426 may store information identifying one or more security requirementsassociated with the network slice, such as, for example, an encryptionrequirement, a requirement to support a particular security protocol, anauthentication and/or authorization requirement, a requirement tosupport protection from a particular security attack, and/or anothertype of security requirement.

Infrastructure field 430 may store information identifying aninfrastructure selected for the network slice by slice admission manager330. Network functions field 440 may store information identifying NFsrequired to implement the network slice. Virtual links field 450 maystore information identifying virtual links required to implement thenetwork slice. Estimated slice load field 460 may store an estimatedslice load computed for the network slice by load estimator 340.

Although FIG. 4 shows exemplary components of slice profile DB 320, inother implementations, slice profile DB 320 may include fewercomponents, different components, additional components, or differentlyarranged components than depicted in FIG. 4.

FIG. 5 illustrates exemplary components of network function DB 350. Asshown in FIG. 5, network function DB 350 may include one or more networkfunction records 500. Each network function record 500 may storeinformation associated with a particular network function. Networkfunction record 500 may include a network function ID field 510, anetwork function type field 520, a deployment field 530, a cloudresources field 540, a RAN resources field 550, a capacity field 560, acurrent load field 570, and a projected future load field 580.

Network function ID field 510 may store information identifying aparticular NF, such as, for example, a unique ID assigned to theparticular NF, an IP address associated with the particular NF, and/oranother type of ID. Network function type field 520 may storeinformation identifying a type of NF associated with the particular NF.For example, network function type field 520 may identify whether theparticular NF corresponds to a DU, a CU, an AMF, an SMF, a UPF, a UDM, aPCF, a CHF, an NEF, an NRF, an NSSF, an NWDAF, and/or another type ofNF.

Deployment field 530 may store information identifying deploymentinformation associated with the particular NF. For example, deploymentfield 530 may identify a particular device or node on which theparticular NF is deployed. Cloud resources field 540 may storeinformation identifying the cloud resources associated with theparticular NF. For example, cloud resources field 540 may identify oneor more processor and/or memory devices associated with the particularNF. RAN resources field 550 may store information identifying RANresources controlled by the particular NF. For example, RAN resourcesfield 550 may identify one or more base station sectors (e.g., RFtransceivers) associated with the particular NF, one or more bandsand/or channels associated with the particular NF, physical resourceblocks (PRBs) associated with the particular NF, a dedicated radiobearers associated with the particular NF, signaling bearers associatedwith the particular NF, and/or other types of RAN resources controlledby the particular NF.

Capacity field 560 may store a capacity associated with the particularNF. For example, capacity field 560 may store information identifying acloud resource capacity associated with the particular NF and/or a RANresource capacity for RAN resources controlled by the particular NF.Current load field 570 may store information identifying a current loadassociated with the particular NF, such as information identifying apercentage of the cloud resources capacity and/or a percentage of theRAN resources capacity associated with the particular NF; informationidentifying a particular KPI value, such as, for example, a processorload value, a memory usage value, a throughput value (e.g., downlinkaverage throughput, downlink maximum throughput, uplink averagethroughput, uplink maximum throughput, etc.), a bandwidth value, anumber of sessions value, a number of PRBs value, a number of dedicatedradio bearers, a number of signal bearers, etc.; and/or other types ofload information. Projected future load field 580 may store informationidentifying a projected future load for the particular NF for anupcoming time period.

Although FIG. 5 shows exemplary components of network function DB 350,in other implementations, network function DB 350 may include fewercomponents, different components, additional components, or differentlyarranged components than depicted in FIG. 5.

FIG. 6 illustrates exemplary components of virtual link DB 360. As shownin FIG. 6, virtual link DB 360 may include one or more virtual linkrecords 600. Each virtual link record 600 may store informationassociated with a particular network function. Virtual link record 600may include a link ID field 610, an endpoints field 620, a deploymentfield 630, a transport resources field 640, a capacity field 650, acurrent load field 660, and a projected future load field 670.

Link ID field 610 may store an ID associated with a particular virtuallink. Endpoints field 620 may identify the endpoints between the virtuallink, such as first NF and a second NF associated with NF records 500 inNF DB 350. Deployment field 630 may store information identifyingdeployment information associated with the particular virtual link, suchas the deployment information associated with the endpoints. Transportresources field 640 may store information identifying transportresources associated with the virtual link, such as, for example, atransport network circuit and/or one or more transport network devices(e.g., routers, switches, ROADMs, etc.), and/or other types of transportnetwork resources.

Capacity field 650 may store a capacity associated with the virtuallink. For example, capacity field 650 may store information identifyinga transport network resource capacity associated with the virtual link,such as throughput capacity of a circuit associated with the virtuallink, a switching capacity associated with a switch, a routing capacityassociated with a router, etc. Current load field 660 may storeinformation identifying a current load associated with the virtual link,such as information identifying a percentage of the transport resourcescapacity; information identifying a particular KPI value, such as, forexample, a throughput value (e.g., downlink average throughput, downlinkmaximum throughput, uplink average throughput, uplink maximumthroughput, etc.), a packet delivery rate value, a packet loss ratevalue, a packet delay rate value, a connection request value (e.g., aconnection request count, a connection request duration, a connectionresponse time, etc.), and/or other types of values indicative of atransport load. Projected future load field 670 may store informationidentifying a projected future load for the virtual link for an upcomingtime period.

Although FIG. 6 shows exemplary components of virtual link DB 360, inother implementations, virtual link DB 360 may include fewer components,different components, additional components, or differently arrangedcomponents than depicted in FIG. 6.

FIG. 7 illustrates a flowchart of a process for network slice admissionaccording to an implementation described herein. In someimplementations, process 700 of FIG. 7 may be performed by orchestrationsystem 170. In other implementations, some or all of process 700 may beperformed by another device or a group of devices separate fromorchestration system 170.

As shown in FIG. 7, process 700 may include receiving a request to admita network slice in a wireless communication network (block 710). Forexample, orchestration system 170 may receive a request to admit a newnetwork slice and may store information relating to the new networkslice in slice profile DB 320. The network slice request may includeinformation identifying one or more requirements associated with thenetwork slice. Process 700 may further include determining requirementsassociated with the network slice (block 720), selecting aninfrastructure on which to deploy the network slice (block 730), anddetermining resources needed to implement the network slice (block 740).For example, orchestration system 170 may select a particularinfrastructure for the new network slice based on the requirementsassociated with the network slice and based on information stored ininfrastructure DB 370 and then identify a set of VNFs and/or virtuallinks between VNFs associated with the infrastructure.

Process 700 may further include computing an estimated resource load forthe network slice (block 750) and computing a current and/or projectedfuture resource load for the determined resources needed to implementthe network slice (block 760). For example, orchestration system 170 maydetermine an estimated load for a network slice based on a capacityrequirement associated with the network slice, such as, for example, aUE device density for a geographic area, a number of UE sessions duringa particular time period, an uplink and/or downlink throughput per UEdevice session, and/or another types of capacity requirement.Orchestration system 170 may convert the capacity requirement into anestimated load for the network slice with respect to cloud resources,transport resources, and/or RAN resources.

Furthermore, orchestration system 170 may determine a projected resourceload for the resources required to implement the network slice based onalready existing network slices. The projected resource load may bebased on a current load and/or a projected future load for the resourcerequired to implement the network slice. Orchestration system 170 maydetermine a load for RAN resources controlled by the identified VNFs,such as, for example, a throughput value, bandwidth value, a number ofPRBs value, a number of dedicated bearers value, a number of signalbearers value, and/or another type of metrics value indicative of a RANresources load; determine a load for cloud resources used by theidentified VNFs, such as, for example, a processor load value, a memoryusage value, and/or another type of metrics value indicative of a cloudresources load; and determine a load for transport resources used by theidentified virtual links, such as, for example, a throughput value, apacket delivery rate value, a packet loss rate value, a packet delayrate value, a connection request value, and/or other types of valuesindicative of a transport load. Additionally, orchestration system 170may determine projected future load values to determine whether the loadvalues may change more than a threshold in an upcoming time period andmay use the projected future load values if the load values aredetermined to be likely to change more than a threshold in the upcomingtime period.

A determination may be made as to whether the resources have sufficientcapacity to meet all the network slice requirements (block 770). Forexample, orchestration system 170 may add up the estimated resource loadfor the network slice and the projected resource load to determine anestimated total load on the resources required to implement the networkslice and compare the estimated total load to slice admission criteriastored in admission criteria DB 385. The slice admission criteria forthe selected infrastructure may specify, for example, a maximum allowedload as a percentage of the total capacity for the resources associatedwith the selected infrastructure.

If it is determined that the resources do not have sufficient capacityto meet all the network slice requirements (block 770—NO), analternative infrastructure may be selected or the network slice may notbe admitted to the wireless communication network (block 775). In someimplementations, orchestration system 170 may select a differentinfrastructure and attempt to admit the network slice on the differentinfrastructure (e.g., by repeating the process of FIG. 7). If adifferent infrastructure is not available, or if all availableinfrastructures have been selected and determined to be unable to meetall the network slice requirements, the network slice may not beadmitted to the wireless communication network. For example,orchestration system 170 may send a message to ordering system 165,indicating that the network slice could not be admitted.

If it is determined that the resources have sufficient capacity to meetthe network slice requirements (block 770—YES), the network slice maynot be admitted to be deployed in the wireless communication network(block 780) and the network slice may be deployed on the selectedinfrastructure (block 790). For example, orchestration system 170 maysend an instruction to deployment system 180 to deploy the network sliceusing the identified resources.

FIG. 8 illustrates an exemplary set 800 of network infrastructures andnetwork slices implemented in core network 150 and/or RAN 130 accordingto an implementation described herein. As shown in FIG. 8,infrastructure set 800 may include an eMBB infrastructure 810, an LLCinfrastructure 850, and a U-LLC infrastructure 870. eMBB infrastructure810 may include base stations 120, transport network devices, and cloudcenter devices hosting NFs for providing eMBB services. Additionalinfrastructures may be deployed on top of eMBB infrastructure 810, suchas an ultra-reliable (UR) infrastructure 812, an ultra-wideband (UWB)infrastructure 814, a high redundancy infrastructure 816, and a highsecurity infrastructure 818. Furthermore, an additional URinfrastructure 820 may be deployed on top of UWB infrastructure 814. URinfrastructure 812 may guarantee ultra-reliable PDU delivery rate (e.g.,about a 99.999% packet delivery rate, about a 99.999% connectionavailability, etc.). UWB infrastructure 814 may enable low energyhigh-bandwidth communication (e.g., over 500 MHz bandwidth) using timemodulation and may provide high data throughput. High redundancyinfrastructure 816 may enable connections with a high redundancy. Highsecurity infrastructure 818 may enable high security connections. UWBinfrastructure 820 may enable UR UWB connections.

eMBB infrastructure 810 may include multiple implemented network slices.For example, eMBB infrastructure 810 may include a best effort (BE) andIMS network slice 830, a V2X infotainment network slice 832, anautomotive original equipment manufacturer (OEM) V2X network slice 834,an enterprise network slice 836, a mission critical (MC) eMBB networkslice 838, and a high density (HD) video streaming network slice 840. BEand IMS network slice 830 may enable BE and/or IMS data traffic. V2Xinfotainment network slice 832 may enable infotainment service topassengers in vehicles. OEM V2X network slice 834 may enable V2Xcommunication for OEMs of vehicles. Enterprise network slice 836 mayenable UE devices 110 to establish private connections to a packet datanetwork 190 associated with an enterprise. MC eMBB network slice 838 maybe implemented on UR infrastructure 812 and enable MC eMBB service(e.g., used by a medical application installed on UE devices 110 ofmedical staff at a hospital, etc.). HD video streaming network slice 840may be implemented on UWB infrastructure 814 and enable HD videostreaming.

LLC infrastructure 850 may include base stations 120, transport networkdevices, and cloud center devices hosting NFs for providing LLC services(e.g., communication with a latency less than 5 milliseconds (ms)).Additional infrastructures may be deployed on top of LLC infrastructure850, such as a UWB infrastructure 852, a UR infrastructure 854, a highredundancy infrastructure 856, and a high security infrastructure 858.UWB infrastructure 852, UR infrastructure 854, high redundancyinfrastructure 856, and high security infrastructure 858 may supportfunctions similar to those described above with respect to eMBB 810.

LLC infrastructure 850 may include multiple implemented network slices.For example, LLC infrastructure 850 may include an augmentedreality/virtual reality (AR/VR) network slice 860, a V2X control networkslice 862, an MC LLC network slice 864, and a gaming slice 866. AR/VRnetwork slice 860 may be implemented on UR infrastructure 854 andprovide an AR/VR service to UE devices 110. V2X control network slice862 may be implemented on UR infrastructure 854 and provide a V2Xcontrol channel that requires low latency messages. MC LLC network slice864 may be implemented on UR infrastructure 854 and enable MC LLCservice (e.g., used by an IoT devices in a manufacturing setting, etc.).Gaming network slice 866 may enable real-time gaming.

U-LLC infrastructure 870 may include base stations 120, transportnetwork devices, and cloud center devices hosting NFs for providingU-LLC services (e.g., communication with a latency less than 1 ms).Additional infrastructures may be deployed on top of U-LLCinfrastructure 870, such as a UWB infrastructure 872, a URinfrastructure 874, a high redundancy infrastructure 876, and a highsecurity infrastructure 878, a UR infrastructure 880, and a URinfrastructure 882. UWB infrastructure 872, UR infrastructure 874, highredundancy infrastructure 876, and high security infrastructure 878 maysupport functions similar to those described above with respect to eMBBinfrastructure 810 and LLC infrastructure 850. UR infrastructure 880 maybe implemented on top of UWB infrastructure 872 and guaranteeultra-reliable and high throughput connections. UR infrastructure 882may be implemented on top of high security infrastructure 878 andguarantee ultra-reliable and high security connections.

U-LLC infrastructure 870 may include multiple implemented networkslices. For example, U-LLC infrastructure 870 may include an AR/VRnetwork slice 884, an MC AR/VR network slice 886, an industry networkslice 888, an industry network slice 890, a trading network slice 892,and a U-LLC network slice 894.

AR/VR network slice 884 may be implemented on UWB infrastructure 872 andprovide a high throughput AR/VR service to UE devices 110. MC AR/VRnetwork slice 886 may be implemented on UR infrastructure 880 and enablemission critical, high reliability, and high throughput AR/VR service(e.g., remote surgery, etc.). Industry network slice 888 may beimplemented on UR infrastructure 880 and enable mission critical, highreliability, and high throughput communication for a particular industryenterprise (e.g., IoT devices controlling robotic devices using computervision, etc.). Industry network slice 890 may be implemented on URinfrastructure 874 and enable high reliability communication for aparticular industry enterprise. Trading network slice 892 may beimplemented on UR infrastructure 882 and enable high speed and highsecurity trading operations. U-LLC network slice 894 may enable U-LLCcommunication not associated with other requirements.

FIG. 9 illustrates a first exemplary signal flow 900 according to animplementation described herein. For example, assume industry networkslice 890 hasn't been admitted yet and ordering system 165 generates arequest to admit industry network slice 890. As shown in FIG. 9, signalflow 900 may include using a service profile 910 to generate a sliceprofile 920 (signal 912). For example, ordering system 165 may generatea slice profile 920 that includes requirements associated with thenetwork slice based on service profile 910. In the case of industrynetwork slice 890, the requirements may include a requirement forultra-low latency and a requirement for ultra-reliable communication.Additionally, the requirements may include a capacity requirement, suchas a throughput requirement, a number of UE sessions per base stationsector requirement etc.

Orchestration system 170 may receive slice profile 920 and select aninfrastructure 930 based on the requirements associated with sliceprofile 920 (signal 924). For example, in the case of industry networkslice 890, orchestration system 170 may select U-LLC infrastructure 870.Orchestration system 170 may then determine NFs 940-A to 940-Nassociated with infrastructure 930, and virtual links 945 between NFs940-A and 940-N, based on information stored in infrastructure DB 370(signals 932, 934, and 936). Virtual link 945-A between NFs 940-A and940-B is shown in FIG. 9 for illustrative purposes.

Orchestration system 170 may use the information stored in networkfunction DB 350 and virtual links DB 360 to determine the resources950-A to 950-N (e.g., cloud resources used by NFs 940 and/or RANresources controlled by NFs 940) associated with NFs 940 and resources955 (e.g., transport resources) associated with virtual links 945(signals 942, 944, 946, and 948). Orchestration system 170 may computean estimated slice load 960 based on the capacity requirements specifiedin slice profile 920 (signal 922) and may determine a projected resourceload for resources 950 and 955 based on load metrics values collectedfrom resources 950 and 955 by analytics engine 185 and/or obtaineddirectly from resources 950 and 955 (signals 952). Additionally, oralternatively, current and/or projected loads for resources 950 and 955may be obtained from another device, such a Network Data AnalyticsFunction (NWDAF) 975 in core network 150 (signal 974).

Thus, projected resource load for resources 950 and 955 may represent apercentage of the total capacity of resources 950 and 955 being used byexisting network slices on infrastructure 930.

Orchestration system 170 may then compare estimated slice load 960 andprojected resource load 970 with the total capacity of resources 950 and955 and slice admission criteria 980 stored in admission criteria DB 385(signals 962 and 972). For example, the slice admission criteria mayspecify that each NF 940 in infrastructure 930 is to maintain a reservecapacity that is a particular percentage of the total capacity. Thus, ifestimated slice load 960 and projected resource load 970 are estimatedto result in a reserve capacity for resources 950 and 955 that satisfiesthe admission criterion, industry network slice 890 may be admitted anddeployed, resulting in slice deployment 990 of industry network slice890 by deployment system 180 (signal 982).

In the preceding specification, various preferred embodiments have beendescribed with reference to the accompanying drawings. It will, however,be evident that various modifications and changes may be made thereto,and additional embodiments may be implemented, without departing fromthe broader scope of the invention as set forth in the claims thatfollow. The specification and drawings are accordingly to be regarded inan illustrative rather than restrictive sense.

For example, while a series of blocks have been described with respectto FIG. 7, and a series of signals have been described with respect toFIG. 9, the order of the blocks, and/or signals, may be modified inother implementations. Further, non-dependent blocks and/or signals maybe performed in parallel.

It will be apparent that systems and/or methods, as described above, maybe implemented in many different forms of software, firmware, andhardware in the implementations illustrated in the figures. The actualsoftware code or specialized control hardware used to implement thesesystems and methods is not limiting of the embodiments. Thus, theoperation and behavior of the systems and methods were described withoutreference to the specific software code—it being understood thatsoftware and control hardware can be designed to implement the systemsand methods based on the description herein.

Further, certain portions, described above, may be implemented as acomponent that performs one or more functions. A component, as usedherein, may include hardware, such as a processor, an ASIC, or a FPGA,or a combination of hardware and software (e.g., a processor executingsoftware).

It should be emphasized that the terms “comprises”/“comprising” whenused in this specification are taken to specify the presence of statedfeatures, integers, steps or components but does not preclude thepresence or addition of one or more other features, integers, steps,components or groups thereof.

The term “logic,” as used herein, may refer to a combination of one ormore processors configured to execute instructions stored in one or morememory devices, may refer to hardwired circuitry, and/or may refer to acombination thereof. Furthermore, a logic may be included in a singledevice or may be distributed across multiple, and possibly remote,devices.

For the purposes of describing and defining the present invention, it isadditionally noted that the term “substantially” is utilized herein torepresent the inherent degree of uncertainty that may be attributed toany quantitative comparison, value, measurement, or otherrepresentation. The term “substantially” is also utilized herein torepresent the degree by which a quantitative representation may varyfrom a stated reference without resulting in a change in the basicfunction of the subject matter at issue.

To the extent the aforementioned embodiments collect, store, or employpersonal information of individuals, it should be understood that suchinformation shall be collected, stored, and used in accordance with allapplicable laws concerning protection of personal information.Additionally, the collection, storage and use of such information may besubject to consent of the individual to such activity, for example,through well known “opt-in” or “opt-out” processes as may be appropriatefor the situation and type of information. Storage and use of personalinformation may be in an appropriately secure manner reflective of thetype of information, for example, through various encryption andanonymization techniques for particularly sensitive information.

No element, act, or instruction used in the present application shouldbe construed as critical or essential to the embodiments unlessexplicitly described as such. Also, as used herein, the article “a” isintended to include one or more items. Further, the phrase “based on” isintended to mean “based, at least in part, on” unless explicitly statedotherwise.

What is claimed is:
 1. A method comprising: receiving a request to admita network slice in a wireless communication network, wherein the networkslice is associated with at least one requirement; determining aplurality of resources, associated with the wireless communicationnetwork, needed to implement the network slice; computing an estimatedresource load for the network slice; computing a projected resource loadfor the determined plurality of resources; determining that theplurality of resources has sufficient capacity to meet the at least onerequirement associated with the network slice based on the computedestimated resource load and the projected resource load for thedetermined plurality of resources; and admitting the network slice to bedeployed in the wireless communication network, in response todetermining that the plurality of resources has sufficient capacity tomeet the at least one requirement associated with the network slice. 2.The method of claim 1, wherein the at least one requirement includes aperformance requirement, a capacity requirement, or a securityrequirement.
 3. The method of claim 1, wherein the plurality ofresources needed to implement the network slice include at least one of:cloud resources; transport resources; or radio access network (RAN)resources.
 4. The method of claim 3, wherein the transport resourcesinclude at least one of a transport network circuit or a transportnetwork device.
 5. The method of claim 3, wherein the RAN resourcesinclude at least one of a base station sector, a wireless communicationband, or a wireless communication channel, a plurality of physicalresource blocks (PRBs), a dedicated radio bearer, or a signaling bearer.6. The method of claim 1, wherein computing an estimated resource loadfor the network slice further includes: determining a plurality ofnetwork functions for the network slice; and determining an estimatedresource load for particular ones of the plurality of network functions.7. The method of claim 6, further comprising: determining a plurality ofvirtual links between the plurality of network functions for the networkslice; and determining an estimated resource load for particular ones ofthe plurality of virtual links.
 8. The method of claim 1, whereincomputing the projected resource load for the determined plurality ofresources further includes: determining a current load for thedetermined plurality of resources; and computing an estimated futureload for the determined plurality of resources based on a historicalload associated with the determined plurality of resources.
 9. Themethod of claim 1, further comprising: selecting a particularinfrastructure, from a plurality of available infrastructures, to deploythe network slice.
 10. The method of claim 9, wherein the particularinfrastructure includes: an enhanced mobile broadband infrastructure, alow latency communication infrastructure, or an ultra-low latencycommunication infrastructure.
 11. A device comprising: a processorconfigured to: receive a request to admit a network slice in a wirelesscommunication network, wherein the network slice is associated with atleast one requirement; determine a plurality of resources, associatedwith the wireless communication network, needed to implement the networkslice; compute an estimated resource load for the network slice; computea projected resource load for the determined plurality of resources;determine that the plurality of resources has sufficient capacity tomeet the at least one requirement associated with the network slicebased on the computed estimated resource load and the projected resourceload for the determined plurality of resources; and admit the networkslice to be deployed in the wireless communication network, in responseto determining that the plurality of resources has sufficient capacityto meet the at least one requirement associated with the network slice.12. The device of claim 11, wherein the at least one requirementincludes a performance requirement, a capacity requirement, or asecurity requirement.
 13. The device of claim 11, wherein the pluralityof resources needed to implement the network slice include at least oneof: cloud resources; transport resources; or radio access network (RAN)resources.
 14. The device of claim 13, wherein the transport resourcesinclude at least one of a transport network circuit or a transportnetwork device.
 15. The device of claim 13, wherein the RAN resourcesinclude at least one of a base station sector, a wireless communicationband, or a wireless communication channel, a plurality of physicalresource blocks (PRBs), a dedicated radio bearer, or a signaling bearer.16. The device of claim 11, wherein, when computing an estimatedresource load for the network slice, the processor is further configuredto: determine a plurality of network functions for the network slice;and determine an estimated resource load for particular ones of theplurality of network functions.
 17. The device of claim 16, wherein theprocessor is further configured to: determine a plurality of virtuallinks between the plurality of network functions for the network slice;and determine an estimated resource load for particular ones of theplurality of virtual links.
 18. The device of claim 11, wherein, whencomputing the projected resource load for the determined plurality ofresources, the processor is further configured to: determine a currentload for the determined plurality of resources; and compute an estimatedfuture load for the determined plurality of resources based on ahistorical load associated with the determined plurality of resources.19. The device of claim 11, wherein the processor is further configuredto: select a particular infrastructure, from a plurality of availableinfrastructures, to deploy the network slice, wherein the particularinfrastructure includes an enhanced mobile broadband infrastructure, alow latency communication infrastructure, or an ultra-low latencycommunication infrastructure.
 20. A non-transitory computer-readablememory device storing instructions executable by a processor, thenon-transitory computer-readable memory device comprising: one or moreinstructions to receive a request to admit a network slice in a wirelesscommunication network, wherein the network slice is associated with atleast one requirement; one or more instructions to determine a pluralityof resources, associated with the wireless communication network, neededto implement the network slice; one or more instructions to compute anestimated resource load for the network slice; one or more instructionsto compute a projected resource load for the determined plurality ofresources; one or more instructions to determine that the plurality ofresources has sufficient capacity to meet the at least one requirementassociated with the network slice based on the computed estimatedresource load and the projected resource load for the determinedplurality of resources; and one or more instructions to admit thenetwork slice to be deployed in the wireless communication network, inresponse to determining that the plurality of resources has sufficientcapacity to meet the at least one requirement associated with thenetwork slice.